摘 要
随着可再生能源在智能电网中的渗透率不断提高，储能系统作为平衡电力供需、提高电能质量的关键技术受到广泛关注。本文针对储能系统优化配置与运行策略展开研究，旨在通过合理的储能规划和调度，提升电网的灵活性与经济性。研究基于多目标优化模型，综合考虑成本最小化、可靠性最大化等约束条件，提出了一种结合遗传算法与粒子群优化的混合智能算法求解方法。通过对典型区域电网的实际案例分析，验证了所提方法的有效性。研究结果表明，该优化配置方案能够在满足电网安全稳定运行的前提下，显著降低运营成本约15%，并有效平抑风电、光伏等间歇性电源带来的功率波动。此外，本文创新性地引入了分时电价机制下的储能充放电策略，为储能系统的商业化运营提供了理论依据和技术支持，对推动智能电网建设具有重要参考价值。
关键词：储能系统优化配置；智能电网；混合智能算法
Abstract
With the increasing penetration of renewable energy in smart grids, energy storage systems (ESS) have garnered significant attention as a critical technology for balancing power supply and demand and improving power quality. This study focuses on the optimal configuration and operation strategies of ESS, aiming to enhance grid flexibility and economic efficiency through rational planning and scheduling. A multi-ob jective optimization model is established, incorporating constraints such as cost minimization and reliability maximization, and a hybrid intelligent algorithm combining genetic algorithms and particle swarm optimization is proposed to solve this model. The effectiveness of the proposed method is validated through case studies of typical regional power grids. The results indicate that this optimal configuration can significantly reduce operational costs by approximately 15% while ensuring safe and stable grid operation, effectively mitigating power fluctuations caused by intermittent sources like wind and photovoltaic power. Additionally, this paper innovatively introduces an ESS charging and discharging strategy under time-of-use electricity pricing mechanisms, providing theoretical support and technical guidance for the commercial operation of ESS, which holds important reference value for promoting the development of smart grids.
Keywords: Optimal Configuration Of Energy Storage Systems；Smart Grid；Hybrid Intelligent Algorithm
目 录
引言 1
一、智能电网储能需求分析 1
（一）储能系统在智能电网中的作用 1
（二）智能电网对储能的需求特性 2
（三）不同场景下的储能需求评估 2
二、储能系统的优化配置研究 2
（一）储能系统配置模型构建 3
（二）关键影响因素分析与量化 3
（三）优化配置方案设计与验证 4
三、储能系统的运行策略研究 4
（一）日内运行调度策略制定 4
（二）多时间尺度协同控制方法 5
（三）紧急情况下的响应策略 5
四、经济性与效益评估分析 5
（一）成本构成与收益来源分析 5
（二）投资回报周期测算方法 6
（三）社会经济效益综合评价 6
结 论 7
致 谢 8
参考文献 9
随着可再生能源在智能电网中的渗透率不断提高，储能系统作为平衡电力供需、提高电能质量的关键技术受到广泛关注。本文针对储能系统优化配置与运行策略展开研究，旨在通过合理的储能规划和调度，提升电网的灵活性与经济性。研究基于多目标优化模型，综合考虑成本最小化、可靠性最大化等约束条件，提出了一种结合遗传算法与粒子群优化的混合智能算法求解方法。通过对典型区域电网的实际案例分析，验证了所提方法的有效性。研究结果表明，该优化配置方案能够在满足电网安全稳定运行的前提下，显著降低运营成本约15%，并有效平抑风电、光伏等间歇性电源带来的功率波动。此外，本文创新性地引入了分时电价机制下的储能充放电策略，为储能系统的商业化运营提供了理论依据和技术支持，对推动智能电网建设具有重要参考价值。
关键词：储能系统优化配置；智能电网；混合智能算法
Abstract
With the increasing penetration of renewable energy in smart grids, energy storage systems (ESS) have garnered significant attention as a critical technology for balancing power supply and demand and improving power quality. This study focuses on the optimal configuration and operation strategies of ESS, aiming to enhance grid flexibility and economic efficiency through rational planning and scheduling. A multi-ob jective optimization model is established, incorporating constraints such as cost minimization and reliability maximization, and a hybrid intelligent algorithm combining genetic algorithms and particle swarm optimization is proposed to solve this model. The effectiveness of the proposed method is validated through case studies of typical regional power grids. The results indicate that this optimal configuration can significantly reduce operational costs by approximately 15% while ensuring safe and stable grid operation, effectively mitigating power fluctuations caused by intermittent sources like wind and photovoltaic power. Additionally, this paper innovatively introduces an ESS charging and discharging strategy under time-of-use electricity pricing mechanisms, providing theoretical support and technical guidance for the commercial operation of ESS, which holds important reference value for promoting the development of smart grids.
Keywords: Optimal Configuration Of Energy Storage Systems；Smart Grid；Hybrid Intelligent Algorithm
目 录
引言 1
一、智能电网储能需求分析 1
（一）储能系统在智能电网中的作用 1
（二）智能电网对储能的需求特性 2
（三）不同场景下的储能需求评估 2
二、储能系统的优化配置研究 2
（一）储能系统配置模型构建 3
（二）关键影响因素分析与量化 3
（三）优化配置方案设计与验证 4
三、储能系统的运行策略研究 4
（一）日内运行调度策略制定 4
（二）多时间尺度协同控制方法 5
（三）紧急情况下的响应策略 5
四、经济性与效益评估分析 5
（一）成本构成与收益来源分析 5
（二）投资回报周期测算方法 6
（三）社会经济效益综合评价 6
结 论 7
致 谢 8
参考文献 9
